[ICLR 2025] From anything to mesh like human artists. Official impl. of "MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers"

Autoregressive Model Beats Diffusion: 🦙 Llama for Scalable Image Generation

[CVPR 2025 Oral]Infinity ∞ : Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis

[NeurIPS 2024]OmniTokenizer: one model and one weight for image-video joint tokenization.

Official PyTorch Implementation of "Scalable Autoregressive Image Generation with Mamba"

[CVPR 2025] CoDe: Collaborative Decoding Makes Visual Auto-Regressive Modeling Efficient

Phase-amplitude coupling (PAC) toolbox

[NeurIPS 2025] ScaleKV: Memory-Efficient Visual Autoregressive Modeling with Scale-Aware KV Cache Compression

[Arxiv'25] MGVQ: Could VQ-VAE Beat VAE? A Generalizable Tokenizer with Multi-group Quantization

Context-aware Biases for Length Extrapolation

Code Implementation for "NASH: A Simple Unified Framework of Structured Pruning for Accelerating Encoder-Decoder Language Models" (EMNLP 2023)

Official PyTorch implementation for "Zero-Shot Styled Text Image Generation, but Make It Autoregressive" (CVPR25)

Graph neural network models to perform link prediction on the nba and ncaa point differential graph on seasons 2013-2019, 2021.

[FG 2024] Finite Scalar Quantization as Facial Tokenizer for Dyadic Reaction Generation

This project demonstrates text summarization using the BART (Bidirectional and Auto-Regressive Transformers) model. BART is a transformer model trained as a denoising autoencoder and is effective for text generation tasks such as summarization.

HMM for the output of HMM Autogressive